Plasma cell-free DNA-based predictors of response to abiraterone acetate/prednisone and prognostic factors in metastatic castration-resistant prostate cancer

Meijun Du, Yijun Tian, Winston Tan, Liewei Wang, Liguo Wang, Deepak Kilari, Chiang Ching Huang, Liang Wang, Manish Kohli

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Background: The combination of abiraterone acetate and prednisone (AA/P) is used to treat metastatic prostate cancer, but molecular predictors of treatment response are not well elucidated. We evaluated plasma circulating tumor DNA- (ctDNA-) based copy number alterations (CNAs) to determine treatment-related predictive and prognostic biomarkers for metastatic castration-resistant prostate cancer (mCRPC). Methods: Serial plasma specimens were prospectively collected from 88 chemotherapy-naive mCRPC patients before and after 12 weeks of AA/P treatment. Sequencing-based CNA analyses were performed on 174 specimens. We evaluated CNA-associated 12-week responses for primary resistance, time to treatment change (TTTC) for secondary resistance, and overall survival for prognosis (P < 0.05). Associations with primary resistance were analyzed using the Fisher exact test. Kaplan–Meier survival curves and Cox regression analyses were used to determine the associations of CNAs with acquired resistance and overall survival. Results: ctDNA reduced by 3.89% in responders and increased by 0.94% in nonresponders (P = 0.0043). Thirty-one prostate cancer-related genes from whole genome CNAs were tested. AR and AR enhancer amplification were associated with primary resistance (P = 0.0039) and shorter TTTC (P = 0.0003). ZFHX3 deletion and PIK3CA amplification were associated with primary resistance (P = 0.026 and P = 0.017, respectively), shorter TTTC (P = 0.0008 and P = 0.0016, respectively), and poor survival (P = 0.0025 and P = 0.0022, respectively). CNA-based risk scores combining selected significant associations (AR, NKX3.1, and PIK3CA) at the univariate level with TTTC were predictive of secondary resistance (P = 0.0002). and established prognoses for survival based on CNAs in ZFHX3, RB1, PIK3CA, and OPHN1 (P = 0.002). Multigene risk scores were more predictive than individual genes or clinical risk factors (P < 0.05). Conclusion: Plasma ctDNA CNAs and risk scores can predict mCRPC-state treatment and survival outcomes.

Original languageEnglish (US)
JournalProstate Cancer and Prostatic Diseases
DOIs
StateAccepted/In press - Jan 1 2020

ASJC Scopus subject areas

  • Oncology
  • Urology
  • Cancer Research

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